Detections

Explore public detection logic contributed by the community across SIEM and rule languages.

3,640 detections

Detects the creation of the 'socks' binary used by the Odyssey Stealer to establish a SOCKS5 proxy for network tunneling on compromised macOS systems. This rule identifies the binary based on specific SHA256 hashes and its filename 'socks'.
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Drew Pilarski@barnabysDrew
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Detections.ai Community
1 year ago
0240
Detects the execution of an application from a mounted disk image (DMG) with a name known to be used by Odyssey Infostealer. This activity is indicative of initial access, where the user has been tricked into running a malicious application masquerading as a legitimate software installer or updater.
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Drew Pilarski@barnabysDrew
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Detections.ai Community
1 year ago
0226
Detects the creation of a randomly named LaunchDaemon .plist file in /Library/LaunchDaemons/, a technique used by Odyssey Stealer for persistence.
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Drew Pilarski@barnabysDrew
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Detections.ai Community
1 year ago
0223
Detects the creation of hidden configuration files used by the Odyssey Infostealer on macOS. These files are known to store sensitive data like passwords, C2 server details, and bot identifiers.
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Drew Pilarski@barnabysDrew
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Detections.ai Community
1 year ago
0220
Detects a file being created in a temporary macOS directory, made executable, and then executed by a shell. This behavior is consistent with the Odyssey Infostealer, which downloads and runs scripts from temporary locations.
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Drew Pilarski@barnabysDrew
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Detections.ai Community
1 year ago
0220
Detects the execution of an AppleScript, characteristic of the Odyssey Stealer, that displays a dialog box prompting the user for their password.
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Dimple g@localhost
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Detections.ai Community
1 year ago
1130
Detects potential Command and Control (C2) communication patterns based on ASIM-normalized network session data in Microsoft Sentinel. This detection covers three primary patterns:

1) Periodic beaconing with low jitter
2) Long-lived HTTP(S) long-polling sessions
3) Network traffic with very consistent payload sizes

Such patterns can indicate covert communication with compromised systems or malware infections.
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Michael Fajkus@MilesDyson
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Detections.ai Community
1 year ago
375314
High confidence that the same actor is responsible for earlier attacks attributed to BlueNoroff and the RustDoor/ThiefBucket and RustBucket campaigns. SentinelLABS observed the use of a novel persistence mechanism abusing the Zsh configuration file zshenv.
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Michael A@JohnMatrix
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Detections.ai Community
1 year ago
3181
Detects files based on common ransomware file extensions or ransom note filenames. This rule is based on a community-sourced list and is intended for broad detection.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
1 year ago
1157
This rule detects attempts by scripting language interpreters (Node.js, Python, PowerShell) to access sensitive browser credential files such as 'Login Data', 'Web Data', and 'Cookies' from Chrome and Brave browser user data directories. It also includes specific file paths that might be associated with known browser extensions or malware that target these files. This activity is indicative of credential dumping or information stealing.
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R W@shiftyroot
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Detections.ai Community
1 year ago
2298
This rule detects when an email with a detected threat (e.g., malware, phishing) has an attachment that is subsequently observed on an endpoint device. This indicates that a malicious attachment from an email was downloaded and executed or saved on a device.
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Ahamed Rizvan@ahamedrizvan
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Detections.ai Community
1 year ago
7093
This rule detects suspicious activity where scripting interpreters (node.exe, python.exe, pwsh.exe, powershell.exe) are observed accessing a large number of potentially sensitive files (e.g., .env, secret, wallet, keypair, credential, recovery files, or common document/data file types like .pdf, .docx, .csv, .json, .txt) and subsequently exfiltrating a significant amount of data over the network. It correlates file access events with network outbound traffic from the same process within a 10-minute window, flagging instances where more than 20 distinct sensitive files are accessed and over 500KB of data is sent out.
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R W@shiftyroot
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Detections.ai Community
1 year ago
1281
This rule identifies devices that have software installed which has reached its End-Of-Support (EOS) status. This is crucial for identifying potential security vulnerabilities due to unpatched software and for maintaining compliance with organizational security policies. The rule summarizes the count of such software instances per device, along with the software name and its End-Of-Support date.
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Ahamed Rizvan@ahamedrizvan
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Detections.ai Community
1 year ago
1056
Detects the use of the 'mdimport' command to index sensitive user directories. This is a key step in the Sploitlight TCC bypass technique (CVE-2025-31199), where a malicious Spotlight importer is triggered to run within the 'mdworker' process and exfiltrate data from TCC-protected locations by writing it to the system log.
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ravi vaghasiya@ravivaghasiya
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Detections.ai Community
1 year ago
4077
Detects the creation or modification of an unsigned Spotlight importer (.mdimporter) bundle within a user's Library/Spotlight directory on macOS. This activity is indicative of the Sploitlight TCC bypass technique (CVE-2025-31199), where an attacker leverages a malicious, unsigned importer to gain unauthorized access to TCC-protected data via the mds/mdworker processes.
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ravi vaghasiya@ravivaghasiya
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Detections.ai Community
1 year ago
5057
Detects the creation of a Spotlight importer bundle (.mdimporter) in a user's Library directory. This is a key step in the Sploitlight TCC bypass technique (CVE-2025-31199), where an attacker places a malicious importer to be executed with elevated privileges by the mds_stores process, allowing unauthorized access to TCC-protected data.
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ravi vaghasiya@ravivaghasiya
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Detections.ai Community
1 year ago
2043
A USB device with Vendor ID 0E90 is associated with vendor WiebeTech (a.k.a "CRU"), which is known to manufacture "mouse jigglers." These hardware devices can be used to prevent a computer from automatically locking the screen or going to sleep. Illegitimate use can range from policy violation to nefarious activity like remote desktop abuse.
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David Wharton@whartond
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Detections.ai Community
1 year ago
53128
The following EQL query can be used to hunt for XMRIG executions within your environment.
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R W@shiftyroot
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Detections.ai Community
1 year ago
6044
Description: Detects the execution of a signed macOS application that subsequently spawns a script interpreter like osascript, sh, or bash. This behavior is uncommon for many legitimate GUI applications but is a known TTP for macOS malware like Odyssey Stealer, which uses signed droppers to execute malicious scripts for credential theft, persistence, and payload delivery.
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Kaung Khant Ko@kaungkhantko
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Detections.ai Community
1 year ago
9174
Detects the installation of specific malicious npm packages associated with the North Korean "Contagious Interview" campaign. These packages are known to deliver the XORIndex malware loader.
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Aaron Mog@AaronMogS2S
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Detections.ai Community
1 year ago
1139
Detects the creation of hidden configuration files or a LaunchDaemon plist file used by the Odyssey Stealer malware to establish persistence on a compromised macOS system.
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Aaron Mog@AaronMogS2S
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Detections.ai Community
1 year ago
0136
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